Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

Remarkable advances have been made in deep learning, leading to the emergence of
highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models …

In recent years, face forgery detectors have aroused great interest and achieved impressive
performance, but they are still struggling with generalization and robustness. In this work, we …

In the rapidly evolving digital landscape, the generation of fake visual, audio, and textual
content poses a significant threat to the trust of society, political stability, and integrity of …

The vigorous developments of the Internet of Things make it possible to extend its computing
and storage capabilities to computing tasks in the aerial system with the collaboration of …

With the rapid development of face forgery techniques, the existing frame-based deepfake
video detection methods have fell into a dilemma that frame-based methods may fail when …

In this work, we propose a novel method to improve the generalization ability of CNN-based
face forgery detectors. Our method considers the feature anomalies of forged faces caused …

This paper proposes a commonality learning strategy for face video forgery detection to
improve the generalization. Considering various face forgery methods could leave certain …

Recently, face manipulation techniques have caused increasing trust concerns in our
society. Although current face manipulation detection methods achieve impressive …

Deep-learning-based super-resolution (SR) methods have been extensively studied and
have achieved significant performance with deep convolutional neural networks. However …